library(httr)
library(jsonlite)
library(countrycode)
library(janitor)
library(readxl)
library(sf)
sf_use_s2(FALSE)
library(tmap)
tmap_mode('view')
library(tidyverse)
options(knitr.kable.NA = '')Data cleaning and auditing
Data cleaning
Read data
raw_metadata <- read_xlsx('data/draft/metada_work_version.xlsx', guess_max = 4000) Check columns
raw_metadata <- raw_metadata %>%
janitor::clean_names() %>%
janitor::remove_empty(c('rows', 'cols')) Check source fields
The fields are: name_orig, format, and language.
- Make sure there are no
\r,\n, other weird characters or typos. - Capitalise and clean
language.
# name
raw_metadata %>%
filter(grepl('http', name_orig)) %>%
group_by(name_orig) %>% count
raw_metadata %>%
filter(is.na(name_orig)) %>%
distinct(url_clean)
raw_metadata %>%
mutate(name_orig = str_squish(name_orig)) %>%
mutate(name_orig = str_remove_all(name_orig, "\\\\")) %>%
mutate(name_orig = str_remove_all(name_orig, "\"")) %>%
group_by(name_orig) %>%
summarise(n_countries = n_distinct(country)) %>%
select(name_orig, n_countries) %>%
print(n=10)
# format
raw_metadata %>%
mutate(format = ifelse(format == 'NA', NA, str_squish(format))) %>%
distinct(format)
# language
raw_metadata %>%
mutate(language = ifelse(language == 'NA', NA, str_squish(language))) %>%
mutate(language = str_replace(language, "/|\\|", ' | ')) %>%
distinct(language) %>%
print(n=50)DOUBTS
The name_orig is: https://www.odonat-grandest.fr/listes-rouges-grand-est-etat-avancement/.
The id values are: [1] 446 447 448 449 450 451 452 453 454 455 456 457.
FIX
# French: Liste rouge des Amphibiens du Grand Est
# English: Red list of Mammals of Grand Est
raw_metadata %>%
mutate(name_orig = ifelse(grepl('htt', name_orig) &
state_province == 'Grand Est',
str_glue('Red list of {group} of Grand Est'), name_orig)) %>%
mutate(name_orig = case_when(grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Birds' ~
'Liste rouge des Oiseaux du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Mammals' ~
'Liste rouge des XXX du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Orthoptera' ~
'',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Fishes' ~
'',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Butterflies' ~
'',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Night butterflies' ~
'',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Ladybugs' ~
'',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Branchiopoda' ~
'',
.default = name_orig))
filter(state_province == 'Grand Est') %>% select(group, name_orig)
raw_metadata %>%
mutate(language = ifelse(language == 'NA', NA, str_squish(language))) %>%
mutate(language = str_replace(language, "/|\\|", ' | ')) %>%
distinct(language)
raw_metadata %>%
mutate(format = ifelse(format == '?', NA, format)) %>%
distinct(format)
raw_metadata %>%
mutate(name_orig = str_squish(name_orig)) %>%
mutate(name_orig = str_remove_all(name_orig, "\\\\")) %>%
mutate(name_orig = str_remove_all(name_orig, "\"")) Check Location fields
The fields are: continent, country, state_province, gadm_level_1, gadm_level_2, region_custom, region_detail, and iso_2.
- Make sure there are no typos, thus duplicates.
- Capitalise
continent,country,state_provincenames.
- Check ISO codes.
- Check GADM levels.
- Clean
region_customandregion_detail.
# check continent
raw_metadata %>%
mutate(continent = str_squish(str_replace_all(str_squish(continent), '\\|', ' | '))) %>%
mutate(continent = str_replace_all(continent, '_', ' ')) %>%
mutate(continent = str_to_title(continent)) %>%
distinct(continent)
# check country
raw_metadata %>%
mutate(country = ifelse(country == 'NA', NA, str_squish(country))) %>%
mutate(country = str_replace_all(country, '_', ' ')) %>%
mutate(country = ifelse(country == 'USSR', NA, str_to_title(country))) %>%
mutate(country = str_replace_all(country, 'And ', 'and ')) %>%
mutate(country = str_replace_all(country, 'Of', 'of')) %>%
mutate(country = str_replace_all(country, 'The', 'the')) %>%
distinct(country)
# check state_province
raw_metadata %>%
mutate(state_province = ifelse(state_province == 'NA', NA, str_squish(state_province))) %>%
mutate(state_province = str_to_title(state_province)) %>%
mutate(state_province = str_replace_all(state_province, 'And ', 'and ')) %>%
mutate(state_province = str_replace_all(state_province, 'Of', 'of')) %>%
mutate(state_province = str_replace_all(state_province, 'The', 'the')) %>%
filter(!is.na(state_province)) %>%
filter(state_province != gadm_level_1) %>%
distinct(country, state_province, gadm_level_1, iso_2, iso_3) %>%
print(n=100)
# check gadm_level_1 and gadm_level_2
raw_metadata %>%
mutate(gadm_level_1 = ifelse(gadm_level_1 == 'NA', NA, str_squish(gadm_level_1))) %>%
mutate(gadm_level_1 = str_to_title(gadm_level_1)) %>%
mutate(gadm_level_1 = str_replace_all(gadm_level_1, 'And ', 'and ')) %>%
mutate(gadm_level_1 = str_replace_all(gadm_level_1, 'Of', 'of')) %>%
mutate(gadm_level_1 = str_replace_all(gadm_level_1, 'The', 'the')) %>%
filter(!is.na(gadm_level_1)) %>% distinct(gadm_level_1) %>%
arrange(gadm_level_1) %>% print(n=100)
raw_metadata %>%
mutate(gadm_level_2 = ifelse(gadm_level_2 == 'NA', NA, str_squish(gadm_level_2))) %>%
mutate(gadm_level_2 = str_to_title(gadm_level_2)) %>%
filter(!is.na(gadm_level_2)) %>% select(gadm_level_2)
# check region_custom and region_detal
raw_metadata %>%
mutate(region_custom = ifelse(region_custom == 'NA', NA, str_squish(region_custom))) %>%
mutate(region_detail = ifelse(region_detail == 'NA', NA, str_squish(region_detail))) %>%
mutate(region_detail = str_squish(str_replace_all(str_squish(region_detail), '\\|', ' | '))) %>%
filter(!is.na(region_custom)) %>%
distinct(region_custom, region_detail, iso_2, iso_3) %>%
print(n=100)
# check iso_2 and iso_3
raw_metadata %>%
janitor::clean_names() %>%
janitor::remove_empty(c('rows', 'cols')) %>%
mutate(iso_2 = ifelse(iso_2 == 'NA' & country != 'Namibia', NA, str_squish(iso_2))) %>%
mutate(iso_2 = str_squish(str_replace_all(str_squish(iso_2), '\\|', ' | '))) %>%
mutate(iso_3 = ifelse(iso_3 == 'NA', NA, str_squish(iso_3))) %>%
mutate(iso_3 = str_squish(str_replace_all(str_squish(iso_3), '\\|', ' | '))) %>%
select(country, iso_2, iso_3, region_custom, region_detail) %>%
filter(is.na(iso_2)) #%>% distinct()DOUBTS
Check Taxon fields
The fields are: kingdom, phylum, subphylum, class, order, and group.
- Check duplicates in all fields.
- Rename
grouptotaxa.
I searched names using the GBIF backbone, using my own custom function nameMatcherGBIF().
# gbif name parser
nameMatcherGBIF <- function(sp_name_list) {
# api <- 'http://api.gbif.org/v1/parser/name'
api <- 'http://api.gbif.org/v1/species/match'
name_parsed <- tibble(sp_name = character(),
scientificName = character(),
kingdom = character(),
phylum = character(),
class = character(),
order = character(),
family = character(),
genus = character(),
specificEpithet = character(),
species = character(),
status = character(),
rank = character())
for(sp_name in sp_name_list){
# cat(sp_name, '\n')
call_url <- str_glue('{api}?name={sp_name}&strict=true&verbose=false')
get_json_call <- GET(url = URLencode(call_url)) %>%
content(as = "text") %>% fromJSON(flatten = TRUE)
if(get_json_call$matchType == 'NONE') {
name_parsed_i <- tibble(sp_name = sp_name,
scientificName = NA,
kingdom = NA,
phylum = NA,
class = NA,
order = NA,
family = NA,
genus = NA,
specificEpithet = NA,
species = NA,
status = NA,
rank = NA)
name_parsed <- rbind(name_parsed, name_parsed_i)
} else{
name_parsed_i <- tibble(sp_name = sp_name,
scientificName = ifelse(exists('scientificName',get_json_call), get_json_call$scientificName, NA),
kingdom = ifelse(exists('kingdom',get_json_call), get_json_call$kingdom, NA),
phylum = ifelse(exists('phylum',get_json_call), get_json_call$phylum, NA),
class = ifelse(exists('class',get_json_call), get_json_call$class, NA),
order = ifelse(exists('order',get_json_call), get_json_call$order, NA),
family = ifelse(exists('family',get_json_call), get_json_call$family, NA),
genus = ifelse(exists('genus',get_json_call), get_json_call$genus, NA),
specificEpithet = ifelse(exists('specificEpithet',get_json_call), get_json_call$specificEpithet, NA),
species = ifelse(exists('species',get_json_call), get_json_call$species, NA),
status = ifelse(exists('status',get_json_call), get_json_call$status, NA),
rank = ifelse(exists('rank',get_json_call), get_json_call$rank, NA))
name_parsed <- rbind(name_parsed, name_parsed_i)
}
}
return(name_parsed)
}
sp_list <- raw_metadata %>%
distinct(kingdom, phylum, subphylum, class, order, group) %>%
mutate(group = str_trim(group)) %>%
mutate(group = str_to_title(group)) %>%
mutate(group = str_replace_all(group, 'And ', 'and ')) %>%
mutate(group = str_replace_all(group, 'Of', 'of')) %>%
mutate(group = str_replace_all(group, 'The', 'the')) %>%
pull(group)
sp_list_matched <- nameMatcherGBIF(sp_list) %>% suppressMessages()
sp_list_matched <- sp_list_matched %>%
mutate(scientificName = case_when(grepl('flora', sp_name, ignore.case=T) ~ 'Plantae',
grepl('fauna', sp_name, ignore.case=T) ~ 'Animalia',
grepl('tunicata', sp_name, ignore.case=T) ~ NA,
.default = scientificName)) %>%
mutate(kingdom = case_when(grepl('flora', sp_name, ignore.case=T) ~ 'Plantae',
grepl('fauna', sp_name, ignore.case=T) ~ 'Animalia',
grepl('tunicata', sp_name, ignore.case=T) ~ NA,
.default = kingdom)) %>%
mutate(phylum = ifelse(phylum == 'chordata', 'Chordata', phylum))
sp_list_unmatched <- sp_list_matched %>%
filter(is.na(scientificName)) %>% pull(sp_name)
sp_list_matched %>% filter(!is.na(kingdom)) %>% nrow() # matched[1] 205
length(sp_list_unmatched) # not matched[1] 358
When the taxon name (i.e., group) was not found I kept the previous taxonomic fields’ values.
merged_list <- left_join(raw_metadata %>%
mutate(group = str_trim(group)) %>%
distinct(group) %>%
arrange(group),
sp_list_matched %>%
filter(!is.na(scientificName)) %>%
rename(group=sp_name) %>% distinct()) %>%
arrange(group)
raw_metadata_taxon_list <- raw_metadata %>%
mutate(group = str_trim(group)) %>%
distinct(group, .keep_all = T) %>%
select(kingdom, phylum, subphylum, class, order, group) %>%
arrange(group)
left_join(raw_metadata %>% mutate(group = str_trim(group)) %>%
select(-c(kingdom,phylum,subphylum,class,order)),
bind_rows(merged_list %>%
filter(!is.na(scientificName)),
merged_list %>%
filter(is.na(scientificName)) %>%
select(group) %>%
left_join(. , raw_metadata_taxon_list))) %>%
mutate(group = str_trim(group)) %>%
mutate(group = str_to_title(group)) %>%
mutate(group = str_replace_all(group, 'And ', 'and ')) %>%
mutate(group = str_replace_all(group, 'Of', 'of')) %>%
mutate(group = str_replace_all(group, 'The', 'the')) %>%
mutate(group = str_replace_all(group, 'Et Al.', 'et al.')) %>%
distinct(group, kingdom, phylum, class, order, family, rank) %>%
arrange(kingdom, phylum, class, order) %>%
kableExtra::kbl(booktabs = T) %>%
kableExtra::kable_styling(latex_options = c('striped', 'hold_position'))| group | kingdom | phylum | class | order | family | rank |
|---|---|---|---|---|---|---|
| Earthworms | Animalia | Anelida | Clitellata | Opisthopora | ||
| Oligochaeta | Animalia | Anelida | Clitellata | |||
| Onychophora | Animalia | Animalia | ||||
| Branchiobdellida | Animalia | Annelida | Clitellata | Branchiobdellida | ORDER | |
| Hirudinea | Animalia | Annelida | Clitellata | |||
| Worms | Animalia | Annelida | Clitellata | |||
| Leech | Animalia | Annelida | Clitellata | |||
| Leeches | Animalia | Annelida | Clitellata | |||
| Echiurida | Animalia | Annelida | Echiura | Echiuroidea | ||
| Sipunculids | Animalia | Annelida | Sipuncula | |||
| Amblypygi | Animalia | Arthropoda | Arachnida | Amblypygi | ORDER | |
| Spiders | Animalia | Arthropoda | Arachnida | Araneae | ||
| Uropodina | Animalia | Arthropoda | Arachnida | Mesostigmata | ||
| Opiliones | Animalia | Arthropoda | Arachnida | Opiliones | ORDER | |
| Opilioness | Animalia | Arthropoda | Arachnida | Opiliones | ||
| Pseudoscorpiones | Animalia | Arthropoda | Arachnida | Pseudoscorpiones | ORDER | |
| False Scorpions | Animalia | Arthropoda | Arachnida | Pseudoscorpions | ||
| Scorpions | Animalia | Arthropoda | Arachnida | Scorpionida | ||
| Arachnida | Animalia | Arthropoda | Arachnida | CLASS | ||
| Anostraca | Animalia | Arthropoda | Branchiopoda | Anostraca | ORDER | |
| Branchiopoda | Animalia | Arthropoda | Branchiopoda | CLASS | ||
| Centipedes | Animalia | Arthropoda | Chilopoda | |||
| Chilopoda | Animalia | Arthropoda | Chilopoda | CLASS | ||
| Collembola | Animalia | Arthropoda | Collembola | CLASS | ||
| Entomostraca | Animalia | Arthropoda | Copepoda | |||
| Copepoda | Animalia | Arthropoda | Copepoda | CLASS | ||
| Millipedes | Animalia | Arthropoda | Diplopoda | |||
| Diplopoda | Animalia | Arthropoda | Diplopoda | CLASS | ||
| Archaeognatha | Animalia | Arthropoda | Insecta | Archaeognatha | ORDER | |
| Blattodea | Animalia | Arthropoda | Insecta | Blattodea | ORDER | |
| Wood Cockroaches | Animalia | Arthropoda | Insecta | Blattodea | ||
| Cockroaches | Animalia | Arthropoda | Insecta | Blattodea | ||
| Hydraenidae | Animalia | Arthropoda | Insecta | Coleoptera | Hydraenidae | FAMILY |
| Coleoptera | Animalia | Arthropoda | Insecta | Coleoptera | ORDER | |
| Carabidae | Animalia | Arthropoda | Insecta | Coleoptera | Carabidae | FAMILY |
| Saproxylic Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Longhorn and Scarab Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Longhorn Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Scarabaeidae | Animalia | Arthropoda | Insecta | Coleoptera | Scarabaeidae | FAMILY |
| Ladybugs | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Water Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Tenebrionidae | Animalia | Arthropoda | Insecta | Coleoptera | Tenebrionidae | FAMILY |
| Soldier Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Leaf Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Histeridae | Animalia | Arthropoda | Insecta | Coleoptera | Histeridae | FAMILY |
| Sphaeritidae | Animalia | Arthropoda | Insecta | Coleoptera | Sphaeritidae | FAMILY |
| Derodontidoidea | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Bostrichoidea | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Staphylinidae | Animalia | Arthropoda | Insecta | Coleoptera | Staphylinidae | FAMILY |
| Lucanidae | Animalia | Arthropoda | Insecta | Coleoptera | Lucanidae | FAMILY |
| Geotrupidae | Animalia | Arthropoda | Insecta | Coleoptera | Geotrupidae | FAMILY |
| Trogidae | Animalia | Arthropoda | Insecta | Coleoptera | Trogidae | FAMILY |
| Silphidae | Animalia | Arthropoda | Insecta | Coleoptera | Silphidae | FAMILY |
| Chrysomelidae | Animalia | Arthropoda | Insecta | Coleoptera | Chrysomelidae | FAMILY |
| Bark Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Ground Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Curculionidae | Animalia | Arthropoda | Insecta | Coleoptera | Curculionidae | FAMILY |
| Powderpost Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Bostrichidae | Animalia | Arthropoda | Insecta | Coleoptera | Bostrichidae | FAMILY |
| Anobiidae | Animalia | Arthropoda | Insecta | Coleoptera | Anobiidae | FAMILY |
| Ptinidae | Animalia | Arthropoda | Insecta | Coleoptera | Ptinidae | FAMILY |
| Deadwood Beetle | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Buprestidae | Animalia | Arthropoda | Insecta | Coleoptera | Buprestidae | FAMILY |
| Snout Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Staphylinoidea | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Cucujoidea | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Lamellicornia | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Seed Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Weevils | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Anthribidae | Animalia | Arthropoda | Insecta | Coleoptera | Anthribidae | FAMILY |
| Platypodidae | Animalia | Arthropoda | Insecta | Coleoptera | Curculionidae | FAMILY |
| Ground Beetle | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Tiger Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Megalopodidae | Animalia | Arthropoda | Insecta | Coleoptera | Megalopodidae | FAMILY |
| Scarabaeoidea | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Cerambycidae | Animalia | Arthropoda | Insecta | Coleoptera | Cerambycidae | FAMILY |
| Curculionoidea | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Cleroidea | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Elateridae | Animalia | Arthropoda | Insecta | Coleoptera | Elateridae | FAMILY |
| Lymexyloidea | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Cicindelidae | Animalia | Arthropoda | Insecta | Coleoptera | Carabidae | FAMILY |
| Lucanoidea | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Hydrophilidae | Animalia | Arthropoda | Insecta | Coleoptera | Hydrophilidae | FAMILY |
| Platypsyllinae | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Cholevinae | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Malachiidae | Animalia | Arthropoda | Insecta | Coleoptera | Malachiidae | FAMILY |
| Melyridae | Animalia | Arthropoda | Insecta | Coleoptera | Melyridae | FAMILY |
| Phloeophilidae | Animalia | Arthropoda | Insecta | Coleoptera | Phloiophilidae | FAMILY |
| Cleridae | Animalia | Arthropoda | Insecta | Coleoptera | Cleridae | FAMILY |
| Cerophytidae | Animalia | Arthropoda | Insecta | Coleoptera | Cerophytidae | FAMILY |
| Eucnemidae | Animalia | Arthropoda | Insecta | Coleoptera | Eucnemidae | FAMILY |
| Cryptophagidae | Animalia | Arthropoda | Insecta | Coleoptera | Cryptophagidae | FAMILY |
| Latridiidae | Animalia | Arthropoda | Insecta | Coleoptera | Latridiidae | FAMILY |
| Mycetophagidae | Animalia | Arthropoda | Insecta | Coleoptera | Mycetophagidae | FAMILY |
| Zopheridae | Animalia | Arthropoda | Insecta | Coleoptera | Zopheridae | FAMILY |
| Monotomidae | Animalia | Arthropoda | Insecta | Coleoptera | Monotomidae | FAMILY |
| Phalacridae | Animalia | Arthropoda | Insecta | Coleoptera | Phalacridae | FAMILY |
| Pyrochroide | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Meloidae | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Orsodacnidae | Animalia | Arthropoda | Insecta | Coleoptera | Orsodacnidae | FAMILY |
| Donaciinae | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Leptinidae | Animalia | Arthropoda | Insecta | Coleoptera | Leiodidae | FAMILY |
| Lissomidae | Animalia | Arthropoda | Insecta | Coleoptera | Elateridae | FAMILY |
| Derodontoidae | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Leiodidae | Animalia | Arthropoda | Insecta | Coleoptera | Leiodidae | FAMILY |
| Oedemeridae | Animalia | Arthropoda | Insecta | Coleoptera | Oedemeridae | FAMILY |
| Melandryidae | Animalia | Arthropoda | Insecta | Coleoptera | Melandryidae | FAMILY |
| Dung Beetles | Animalia | Arthropoda | Insecta | Coleoptera | ||
| Earwigs | Animalia | Arthropoda | Insecta | Dermaptera | ||
| Heteroptera | Animalia | Arthropoda | Insecta | Diptera | Sphaeroceridae | GENUS |
| Acalyptratae | Animalia | Arthropoda | Insecta | Diptera | ||
| Calypterate | Animalia | Arthropoda | Insecta | Diptera | ||
| Larger Brachycera | Animalia | Arthropoda | Insecta | Diptera | ||
| Dolichopodid | Animalia | Arthropoda | Insecta | Diptera | ||
| Lonchopteridae | Animalia | Arthropoda | Insecta | Diptera | Lonchopteridae | FAMILY |
| Platypezidae | Animalia | Arthropoda | Insecta | Diptera | Platypezidae | FAMILY |
| Opetiidae | Animalia | Arthropoda | Insecta | Diptera | Opetiidae | FAMILY |
| Hoverflies | Animalia | Arthropoda | Insecta | Diptera | ||
| Chaoboridae | Animalia | Arthropoda | Insecta | Diptera | Chaoboridae | FAMILY |
| Thaumaleidae | Animalia | Arthropoda | Insecta | Diptera | Thaumaleidae | FAMILY |
| Ceratopogonidae | Animalia | Arthropoda | Insecta | Diptera | Ceratopogonidae | FAMILY |
| Flies | Animalia | Arthropoda | Insecta | Diptera | ||
| Asilidae | Animalia | Arthropoda | Insecta | Diptera | Asilidae | FAMILY |
| Psychodidae | Animalia | Arthropoda | Insecta | Diptera | Psychodidae | FAMILY |
| Dixidae | Animalia | Arthropoda | Insecta | Diptera | Dixidae | FAMILY |
| Soldier Flies | Animalia | Arthropoda | Insecta | Diptera | ||
| Horse-Flies | Animalia | Arthropoda | Insecta | Diptera | ||
| Bee Flies | Animalia | Arthropoda | Insecta | Diptera | ||
| Empididae | Animalia | Arthropoda | Insecta | Diptera | Empididae | FAMILY |
| Conopidae | Animalia | Arthropoda | Insecta | Diptera | Conopidae | FAMILY |
| Chironomidae | Animalia | Arthropoda | Insecta | Diptera | Chironomidae | FAMILY |
| Dolichopodidae | Animalia | Arthropoda | Insecta | Diptera | Dolichopodidae | FAMILY |
| Black Flies | Animalia | Arthropoda | Insecta | Diptera | ||
| Long-Legged Flies | Animalia | Arthropoda | Insecta | Diptera | ||
| Micropezidae | Animalia | Arthropoda | Insecta | Diptera | Micropezidae | FAMILY |
| Grass Flies | Animalia | Arthropoda | Insecta | Diptera | ||
| Tachinidae | Animalia | Arthropoda | Insecta | Diptera | Tachinidae | FAMILY |
| Aquatic Empididae | Animalia | Arthropoda | Insecta | Diptera | ||
| Pediciidae | Animalia | Arthropoda | Insecta | Diptera | Pediciidae | FAMILY |
| Limoniidae | Animalia | Arthropoda | Insecta | Diptera | Limoniidae | FAMILY |
| Diptera | Animalia | Arthropoda | Insecta | Diptera | ||
| Parasitic Diptera | Animalia | Arthropoda | Insecta | Diptera | ||
| Mayflies | Animalia | Arthropoda | Insecta | Ephemeroptera | ||
| Auchenorrhyncha | Animalia | Arthropoda | Insecta | Hemiptera | ||
| Cicadas | Animalia | Arthropoda | Insecta | Hemiptera | ||
| Shieldbugs | Animalia | Arthropoda | Insecta | Hemiptera | ||
| Clavicornia | Animalia | Arthropoda | Insecta | Hemiptera | Aradidae | GENUS |
| Big-Eyed Bugs | Animalia | Arthropoda | Insecta | Hemiptera | ||
| Nepomorpha | Animalia | Arthropoda | Insecta | Hemiptera | ||
| Fulgoromorpha | Animalia | Arthropoda | Insecta | Hemiptera | ||
| Cicadomorpha | Animalia | Arthropoda | Insecta | Hemiptera | Palaeontinidae | GENUS |
| Scale Insect | Animalia | Arthropoda | Insecta | Hemiptera | ||
| Hemiptera | Animalia | Arthropoda | Insecta | Hemiptera | ORDER | |
| Ants | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Bombus Spp. | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Hymenoptera | Animalia | Arthropoda | Insecta | Hymenoptera | ORDER | |
| Bees | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Diversicornia | Animalia | Arthropoda | Insecta | Hymenoptera | Encyrtidae | GENUS |
| Sawflies | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Spheciformes | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Pompilidae | Animalia | Arthropoda | Insecta | Hymenoptera | Pompilidae | FAMILY |
| Chrysididae | Animalia | Arthropoda | Insecta | Hymenoptera | Chrysididae | FAMILY |
| Scolioidea | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Cuckoo Wasp | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Wasps | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Sphecidae | Animalia | Arthropoda | Insecta | Hymenoptera | Sphecidae | FAMILY |
| Wild Bees | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Scoliidae | Animalia | Arthropoda | Insecta | Hymenoptera | Scoliidae | FAMILY |
| Crabronidae et al. | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Chrysididae et al. | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Symphyta | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Stinging Wasps | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Mutillidae | Animalia | Arthropoda | Insecta | Hymenoptera | Mutillidae | FAMILY |
| Sapygidae | Animalia | Arthropoda | Insecta | Hymenoptera | Sapygidae | FAMILY |
| Tiphiidae | Animalia | Arthropoda | Insecta | Hymenoptera | Tiphiidae | FAMILY |
| Cimbicidae | Animalia | Arthropoda | Insecta | Hymenoptera | Cimbicidae | FAMILY |
| Siricidae | Animalia | Arthropoda | Insecta | Hymenoptera | Siricidae | FAMILY |
| Xiphydriidae | Animalia | Arthropoda | Insecta | Hymenoptera | Xiphydriidae | FAMILY |
| Ampulicidae | Animalia | Arthropoda | Insecta | Hymenoptera | Ampulicidae | FAMILY |
| Crabronidae | Animalia | Arthropoda | Insecta | Hymenoptera | Crabronidae | FAMILY |
| Apoidea | Animalia | Arthropoda | Insecta | Hymenoptera | ||
| Lepidoptera | Animalia | Arthropoda | Insecta | Lepidoptera | ORDER | |
| Moths | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Butterflies | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Papilionoidea | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Hesperioidea | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Noctuidae | Animalia | Arthropoda | Insecta | Lepidoptera | Noctuidae | FAMILY |
| Night Butterflies | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Owlet Moths | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Lymantriinae | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Short-Cloaked Moth | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Geometer Moths | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Bombyces | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Sphinges S.l. | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Pyralidae | Animalia | Arthropoda | Insecta | Lepidoptera | Pyralidae | FAMILY |
| Sphinges | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Geometridae | Animalia | Arthropoda | Insecta | Lepidoptera | Geometridae | FAMILY |
| Makrolepidoptera | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Macrolepidoptera | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Microlepidoptera | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Zygaenidae | Animalia | Arthropoda | Insecta | Lepidoptera | Zygaenidae | FAMILY |
| Sphingidae | Animalia | Arthropoda | Insecta | Lepidoptera | Sphingidae | FAMILY |
| Sesiidae | Animalia | Arthropoda | Insecta | Lepidoptera | Sesiidae | FAMILY |
| Psychidae | Animalia | Arthropoda | Insecta | Lepidoptera | Psychidae | FAMILY |
| Pterophoridae | Animalia | Arthropoda | Insecta | Lepidoptera | Pterophoridae | FAMILY |
| Alucitidae | Animalia | Arthropoda | Insecta | Lepidoptera | Alucitidae | FAMILY |
| Crambidae | Animalia | Arthropoda | Insecta | Lepidoptera | Crambidae | FAMILY |
| Torticidae | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Choreutidae | Animalia | Arthropoda | Insecta | Lepidoptera | Choreutidae | FAMILY |
| Hawk Moths | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Bombycidae | Animalia | Arthropoda | Insecta | Lepidoptera | Bombycidae | FAMILY |
| Pantheidae | Animalia | Arthropoda | Insecta | Lepidoptera | Noctuidae | FAMILY |
| Nolidae | Animalia | Arthropoda | Insecta | Lepidoptera | Nolidae | FAMILY |
| Sessidae | Animalia | Arthropoda | Insecta | Lepidoptera | ||
| Erebidae | Animalia | Arthropoda | Insecta | Lepidoptera | Erebidae | FAMILY |
| Mantodea | Animalia | Arthropoda | Insecta | Mantodea | ORDER | |
| Mecoptera | Animalia | Arthropoda | Insecta | Mecoptera | ORDER | |
| Scorpionflies | Animalia | Arthropoda | Insecta | Mecoptera | ||
| Megaloptera | Animalia | Arthropoda | Insecta | Megaloptera | ||
| Neuroptera | Animalia | Arthropoda | Insecta | Neuroptera | ORDER | |
| Owlflies | Animalia | Arthropoda | Insecta | Neuroptera | ||
| Net-Winged Insects | Animalia | Arthropoda | Insecta | Neuroptera | ||
| Odonata | Animalia | Arthropoda | Insecta | Odonata | ORDER | |
| Orthoptera | Animalia | Arthropoda | Insecta | Orthoptera | ORDER | |
| Grasshoppers | Animalia | Arthropoda | Insecta | Orthoptera | ||
| Ensifera | Animalia | Arthropoda | Insecta | Orthoptera | ||
| Caelifera | Animalia | Arthropoda | Insecta | Orthoptera | ||
| Crickets | Animalia | Arthropoda | Insecta | Orthoptera | ||
| Katydids | Animalia | Arthropoda | Insecta | Orthoptera | ||
| Stick Insects | Animalia | Arthropoda | Insecta | Phasmatodea | ||
| Stoneflies | Animalia | Arthropoda | Insecta | Plecoptera | ||
| Snakeflies | Animalia | Arthropoda | Insecta | Raphidioptera | ||
| Thrips | Animalia | Arthropoda | Insecta | Thysanoptera | Thripidae | GENUS |
| Trichoptera | Animalia | Arthropoda | Insecta | Trichoptera | ORDER | |
| Caddisflies | Animalia | Arthropoda | Insecta | Trichoptera | ||
| Plecoptera | Animalia | Arthropoda | Insecta | CLASS | ||
| Insects | Animalia | Arthropoda | Insecta | |||
| Aquatic and Semi-Aquatic Bugs | Animalia | Arthropoda | Insecta | |||
| Insecta | Animalia | Arthropoda | Insecta | CLASS | ||
| Water Bugs | Animalia | Arthropoda | Insecta | |||
| Woodlice | Animalia | Arthropoda | Isopoda | |||
| Amphipoda | Animalia | Arthropoda | Malacostraca | Amphipoda | ORDER | |
| Niphargidae | Animalia | Arthropoda | Malacostraca | Amphipoda | Niphargidae | FAMILY |
| Cumacea | Animalia | Arthropoda | Malacostraca | Cumacea | ORDER | |
| Decapoda | Animalia | Arthropoda | Malacostraca | Decapoda | ORDER | |
| Crayfishes | Animalia | Arthropoda | Malacostraca | Decapoda | ||
| Astacoidea | Animalia | Arthropoda | Malacostraca | Decapoda | ||
| Freshwater Decapod Crustaceans | Animalia | Arthropoda | Malacostraca | Decapoda | ||
| Marine Decapod Crustaceans | Animalia | Arthropoda | Malacostraca | Decapoda | ||
| Marine Isopoda | Animalia | Arthropoda | Malacostraca | Isopoda | ||
| Malacostraca | Animalia | Arthropoda | Malacostraca | CLASS | ||
| Mysidacea | Animalia | Arthropoda | Malacostraca | CLASS | ||
| Barnacles | Animalia | Arthropoda | Thecostraca | |||
| Freshwater Crabs | Animalia | Arthropoda | Decapoda | |||
| Horseshoe Crabs | Animalia | Arthropoda | Xiphosura | |||
| Crustaceans | Animalia | Arthropoda | ||||
| Arthropods | Animalia | Arthropoda | ||||
| Freshwater Crustaceans | Animalia | Arthropoda | ||||
| Crayfish | Animalia | Arthropoda | ||||
| Sea Spiders | Animalia | Arthropoda | ||||
| Marine Crustaceans | Animalia | Arthropoda | ||||
| Miscellaneous Arthropods | Animalia | Arthropoda | ||||
| Myriapods | Animalia | Arthropoda | ||||
| Brachiopods | Animalia | Brachiopoda | ||||
| Marine Bryozoans | Animalia | Bryoza | ||||
| Bryozoa | Animalia | Bryozoa | PHYLUM | |||
| Bony Fishes | Animalia | Chordata | Actinopterygii | |||
| Frogs | Animalia | Chordata | Amphibia | Anura | ||
| Amphibians | Animalia | Chordata | Amphibia | |||
| Sea Squirts | Animalia | Chordata | Ascidiacea | |||
| Anatidae | Animalia | Chordata | Aves | Anseriformes | Anatidae | FAMILY |
| Galliformes | Animalia | Chordata | Aves | Galliformes | ORDER | |
| Birds | Animalia | Chordata | Aves | |||
| Breeding Birds | Animalia | Chordata | Aves | |||
| Wintering Birds | Animalia | Chordata | Aves | |||
| Transient Birds | Animalia | Chordata | Aves | |||
| Birds Terre Adelie | Animalia | Chordata | Aves | |||
| Birds Terres Australes | Animalia | Chordata | Aves | |||
| Birds Scattered Islands | Animalia | Chordata | Aves | |||
| Migratory Birds | Animalia | Chordata | Aves | |||
| Metropolitan Birds | Animalia | Chordata | Aves | |||
| Endemic Brids | Animalia | Chordata | Aves | |||
| Breeding Birds of Prey | Animalia | Chordata | Aves | |||
| Endangered Birds | Animalia | Chordata | Aves | |||
| Birds Ecuador | Animalia | Chordata | Aves | |||
| Birds Galapagos | Animalia | Chordata | Aves | |||
| Birds of Prey | Animalia | Chordata | Aves | |||
| Breeding Raptors | Animalia | Chordata | Aves | |||
| Freshwater Lamprey | Animalia | Chordata | Cephalaspidomorphi | |||
| Sharks | Animalia | Chordata | Chondrichthyes | |||
| Chondrichthyes | Animalia | Chordata | Chondrichthyes | |||
| Lamprey | Animalia | Chordata | Hyperoartia | |||
| Cetaceans | Animalia | Chordata | Mammalia | Artiodactyla | ||
| Bats | Animalia | Chordata | Mammalia | Chiroptera | ||
| Perissodactyla | Animalia | Chordata | Mammalia | Perissodactyla | ORDER | |
| Primates | Animalia | Chordata | Mammalia | Primates | ORDER | |
| Lemurs | Animalia | Chordata | Mammalia | Primates | ||
| Rodents | Animalia | Chordata | Mammalia | Rodentia | ||
| Mammals | Animalia | Chordata | Mammalia | |||
| Terrestrial Mammals | Animalia | Chordata | Mammalia | |||
| Marine Mammals | Animalia | Chordata | Mammalia | |||
| Mammals Scattered Islands | Animalia | Chordata | Mammalia | |||
| Terrestial Mammals | Animalia | Chordata | Mammalia | |||
| Aquatic Mammals | Animalia | Chordata | Mammalia | |||
| Metropolitan Mammals | Animalia | Chordata | Mammalia | |||
| Endemic Mammals | Animalia | Chordata | Mammalia | |||
| Large Mammals | Animalia | Chordata | Mammalia | |||
| Insectivores | Animalia | Chordata | Mammalia | |||
| Carnivores | Animalia | Chordata | Mammalia | |||
| Marine Cetartiodactyla | Animalia | Chordata | Mammalia | |||
| Terrestrial Cetartiodactyla | Animalia | Chordata | Mammalia | |||
| Proboscidea & Sirenia | Animalia | Chordata | Mammalia | |||
| Endangered Mammals | Animalia | Chordata | Mammalia | |||
| Ungulates | Animalia | Chordata | Mammalia | |||
| Land Mammals | Animalia | Chordata | Mammalia | |||
| Caimans | Animalia | Chordata | Reptilia | Crocodilia | ||
| Chameleons | Animalia | Chordata | Reptilia | Squamata | ||
| Lizards and Worm-Lizards | Animalia | Chordata | Reptilia | Squamata | ||
| Snakes | Animalia | Chordata | Reptilia | Squamata | ||
| Marine Turtles | Animalia | Chordata | Reptilia | Testudines | ||
| Turtles | Animalia | Chordata | Reptilia | Testudines | ||
| Sea Turtles | Animalia | Chordata | Reptilia | Testudines | ||
| Reptiles | Animalia | Chordata | Reptilia | |||
| Terrestrial Reptiles | Animalia | Chordata | Reptilia | |||
| Endemic Lizards | Animalia | Chordata | Reptilia | |||
| Endemic Reptiles | Animalia | Chordata | Reptilia | |||
| Fishes | Animalia | Chordata | ||||
| Lampreys | Animalia | Chordata | ||||
| Freshwater Fishes | Animalia | Chordata | ||||
| Marine Fishes | Animalia | Chordata | ||||
| Tunicata | Animalia | Chordata | ||||
| Lancelets | Animalia | Chordata | ||||
| Reef Fishes | Animalia | Chordata | ||||
| Terrestrial Vertebrates | Animalia | Chordata | ||||
| Freshwater and Migratory Fishes | Animalia | Chordata | ||||
| Cyclostomata | Animalia | Chordata | ||||
| Endangered Vertebrates | Animalia | Chordata | ||||
| Endemic Freshwater Fishes | Animalia | Chordata | ||||
| Linefishes | Animalia | Chordata | ||||
| Brackish and Freshwater Fishes | Animalia | Chordata | ||||
| Corals | Animalia | Cnidaria | ||||
| Cnidaria | Animalia | Cnidaria | PHYLUM | |||
| Reef Corals | Animalia | Cnidaria | ||||
| Marine Cnidaria | Animalia | Cnidaria | ||||
| Echinoderms | Animalia | Echinodermata | ||||
| Acorn Worms | Animalia | Hemichordata | Enteropneusta | |||
| Bivalvia | Animalia | Mollusca | Bivalvia | CLASS | ||
| Marine Bivalves | Animalia | Mollusca | Bivalvia | |||
| Mussels | Animalia | Mollusca | Bivalvia | |||
| Musslels | Animalia | Mollusca | Bivalvia | |||
| Cephalopods | Animalia | Mollusca | Cephalopoda | |||
| Gastropoda | Animalia | Mollusca | Gastropoda | CLASS | ||
| Snails | Animalia | Mollusca | Gastropoda | |||
| Marine Snails | Animalia | Mollusca | Gastropoda | |||
| Terrestrial Gastropods | Animalia | Mollusca | Gastropoda | |||
| Freshwater Gastropods | Animalia | Mollusca | Gastropoda | |||
| Mollusca | Animalia | Mollusca | PHYLUM | |||
| Molluscs | Animalia | Mollusca | ||||
| Terrestrial Molluscs | Animalia | Mollusca | ||||
| Non-Marine Molluscs | Animalia | Mollusca | ||||
| Inland Molluscs | Animalia | Mollusca | ||||
| Species-Poor Groups of Marine Molluscs | Animalia | Mollusca | ||||
| Freswater Mollusc | Animalia | Mollusca | ||||
| Extramarine Molluscs | Animalia | Mollusca | ||||
| Nematoda | Animalia | Nematoda | PHYLUM | |||
| Ribbon Worms | Animalia | Nemertea | ||||
| Flatworms | Animalia | Platyhelminthes | Turbellaria | |||
| Porifera | Animalia | Porifera | PHYLUM | |||
| Sea Sponges | Animalia | Porifera | ||||
| Vertebrates | Animalia | chordata | ||||
| Fauna | Animalia | |||||
| Cave Fauna | Animalia | |||||
| Polychaeta | Animalia | KINGDOM | ||||
| Invertebrates | Animalia | |||||
| Fauna_en_higher | Animalia | |||||
| Fauna_nt_lc_dd | Animalia | |||||
| Fauna_en_vu | Animalia | |||||
| Terrestrial Invertebrates | Animalia | |||||
| Aquatic Invertebrates | Animalia | |||||
| Fauna_flagship Species | Animalia | |||||
| Endemic Fauna | Animalia | |||||
| Protected Animals | Animalia | |||||
| Endangered Fauna | Animalia | |||||
| Selected Species | Animalia | |||||
| Marine Species | Animalia | |||||
| Endangered Species | Animalia | |||||
| Marine Invertebrates | Animalia | |||||
| Freshwater Plants | Animalia | |||||
| Flora Visiting Fauna | Animalia | |||||
| Other Invertebrates | Animalia | |||||
| Other Marine Invertebrates | Animalia | |||||
| Marine Fauna | Animalia | |||||
| Endemic Animals | Animalia | |||||
| Vaucheriaceae | Chromista | Ochrophyta | Xanthophyceae | Vaucheriales | Vaucheriaceae | FAMILY |
| Ascomycota | Fungi | Ascomycota | PHYLUM | |||
| Agaricales | Fungi | Basidiomycota | Agaricomycetes | Agaricales | ORDER | |
| Boletaceae | Fungi | Basidiomycota | Agaricomycetes | Boletales | Boletaceae | FAMILY |
| Boletales | Fungi | Basidiomycota | Agaricomycetes | Boletales | ORDER | |
| Russulales | Fungi | Basidiomycota | Agaricomycetes | Russulales | ORDER | |
| Ustilaginales | Fungi | Basidiomycota | Ustilaginomycetes | Ustilaginales | ORDER | |
| Basidiomycota | Fungi | Basidiomycota | PHYLUM | |||
| Fungi | Fungi | KINGDOM | ||||
| Macromycetes | Fungi | |||||
| Mushrooms | Fungi | |||||
| Macrofungi | Fungi | |||||
| Phytoparasitic Small Fungi | Fungi | |||||
| Large Mushrooms | Fungi | |||||
| Lichenicolous Fungus | Fungi | |||||
| Ascomycetes | Fungi | |||||
| Aphyllophorales | Fungi | |||||
| Phytoparasitic Microfungi | Fungi | |||||
| Characeae | Plantae | Charophyta | Charophyceae | Charales | Characeae | FAMILY |
| Charophyceae | Plantae | Charophyta | Charophyceae | CLASS | ||
| Desmidiales | Plantae | Charophyta | Conjugatophyceae | Desmidiales | ORDER | |
| Zygnematophyceae | Plantae | Charophyta | Zygnematophyceae | CLASS | ||
| Freshwater Diatoms | Plantae | Gyrista | Bacillariophyceae | |||
| Marchantiophyta | Plantae | Marchantiophyta | PHYLUM | |||
| Apiaceae | Plantae | Tracheophyta | Magnoliopsida | Apiales | Apiaceae | FAMILY |
| Cactaceae | Plantae | Tracheophyta | Magnoliopsida | Caryophyllales | Cactaceae | FAMILY |
| Magnoliaceae | Plantae | Tracheophyta | Magnoliopsida | Magnoliales | Magnoliaceae | FAMILY |
| Anisoptera | Plantae | Tracheophyta | Magnoliopsida | Malvales | Dipterocarpaceae | GENUS |
| Dipterocarpaceae | Plantae | Tracheophyta | Magnoliopsida | Malvales | Dipterocarpaceae | FAMILY |
| Magnoliophyta | Plantae | Tracheophyta | PHYLUM | |||
| Charophytes | Plantae | Charophyceae | Charales | |||
| Lycopods | Plantae | Lycopodiopsida | Lycopodiales | |||
| Tree Ferns | Plantae | Polypodiopsida | ||||
| Sphagnum Mosses | Plantae | Sphagnopsida | ||||
| Orchids | Plantae | Asparagales | ||||
| Wild Cinnamon | Plantae | Laurales | ||||
| Bromeliads | Plantae | Poales | ||||
| Flora | Plantae | |||||
| Bryophytes | Plantae | |||||
| Ferns | Plantae | |||||
| Vascular Plants | Plantae | |||||
| Lichens | Plantae | |||||
| Hydrophytes | Plantae | |||||
| Marine Flora | Plantae | |||||
| Hornworts | Plantae | |||||
| Liverworts | Plantae | |||||
| Mosses | Plantae | |||||
| Flora Saint Paul and Amsterdam | Plantae | |||||
| Flora Scattered Islands | Plantae | |||||
| Flora Kerguelen | Plantae | |||||
| Endemic Flora | Plantae | |||||
| Trees | Plantae | |||||
| Shrubs | Plantae | |||||
| Algae | Plantae | |||||
| Arctic Vascular Plants | Plantae | |||||
| Marine Macroalgae | Plantae | |||||
| Freshwater Red Algae | Plantae | |||||
| Freshwater Brown Algae | Plantae | |||||
| Flowering Plant | Plantae | |||||
| Red Algae | Plantae | |||||
| Brown Algae | Plantae | |||||
| Hepaticophyta | Plantae | |||||
| Broad-Leaved Mosses | Plantae | |||||
| Lichen Communities | Plantae | |||||
| Flora of Cerrado Biom | Plantae | |||||
| Endemic Plants | Plantae | |||||
| Flora On the Red List | Plantae | |||||
| Protected Plants | Plantae | |||||
| Endangered Plants | Plantae | |||||
| Near-Endemic Flora | Plantae | |||||
| Perennial Shrubs | Plantae | |||||
| Flora_2 | Plantae | |||||
| Endemic and Range-Restricted Vascular Plantss | Plantae | |||||
| Indigenous Plants | Plantae | |||||
| Selected Species In Marshlands | Plantae | |||||
| Conifers | Plantae | |||||
| Peninsular Planrs | Plantae | |||||
| Lycophytes | Plantae | |||||
| Higher Plants | Plantae | |||||
| Cloud Forest Trees | Plantae | |||||
| Spermatophytes | Plantae | |||||
| Palms | Plantae | |||||
| Wild Crop Relatives | Plantae | |||||
| Aquatic Plants | Plantae | |||||
| Medicinal Plants | Plantae | |||||
| Dry Forest Trees | Plantae | |||||
| Monocotyledons | Plantae | |||||
| Freshwater Flora | Plantae | |||||
| Flora List | Plantae | |||||
| Endemic Trees | Plantae | |||||
| Myxomycetes | Protozoa | Mycetozoa | Myxomycetes | CLASS | ||
| Protozoa | Protozoa | KINGDOM | ||||
| Zygoptera | Protozoa | GENUS |
FIX
raw_metadata %>%
mutate(kingdom = ifelse(group == 'Flora', 'Plantae', kingdom)) %>%
mutate(kingdom = ifelse(group == 'Fauna', 'Animalia', kingdom)) %>%
mutate(phylum = ifelse(group == 'Flora' | group == 'Fauna', NA, phylum)) %>%
mutate(phylum = ifelse(group =='Onychophora', 'Onychophora', phylum)) %>%
mutate(group = ifelse(group =='Opilioness', 'Opiliones', group)) %>%
mutate(group = ifelse(group =='False scorpions', 'Pseudoscorpiones', group)) %>%
mutate(order = ifelse(group =='False scorpions', 'Pseudoscorpiones', order)) %>%
mutate(class = ifelse(group =='Entomostraca', NA, class)) %>%
mutate(class = ifelse(group =='Horseshoe Crabs', 'Merostomata', class)) %>%
mutate(class = ifelse(group =='Freshwater Crabs', 'Malacostraca', class)) %>%
mutate(class = ifelse(group =='Sharks', 'Chondrichthyes', class)) %>%
mutate(order = ifelse(iso_2 == 'KE' & group == 'Carnivores', 'Carnivora', order),
order = ifelse(iso_2 == 'KE' & group == 'Perissodactyla', 'Perissodactyla', order),
order = ifelse(iso_2 == 'KE' & group == 'Marine Cetartiodactyla', 'Artiodactyla', order),
order = ifelse(iso_2 == 'KE' & group == 'Terrestrial Cetartiodactyla', 'Artiodactyla', order)) %>%
mutate(group = ifelse(group == 'Marine Cetartiodactyla', 'Cetaceans', group),
group = ifelse(group == 'Terrestrial Cetartiodactyla', 'Ungulates', group)) %>%
mutate(order = ifelse(group =='Endemic Lizards', 'Squamata', order)) %>%
mutate(class = ifelse(grepl('lamprey', ignore.case=T, group), 'Petromyzonti', class),
order = ifelse(grepl('lamprey', ignore.case=T, group), 'Petromyzontiformes', order)) %>%
mutate(group = ifelse(group == 'Musslels', 'Mussels', group)) %>%
mutate(phylum = ifelse(grepl('orchid', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('orchid', ignore.case=T, group), 'Liliopsida', class),
order = ifelse(grepl('orchid', ignore.case=T, group), 'Asparagales', order)) %>%
mutate(phylum = ifelse(grepl('bromeli', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('bromeli', ignore.case=T, group), 'Liliopsida', class)) %>%
mutate(phylum = ifelse(grepl('cinnamon', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('cinnamon', ignore.case=T, group), 'Magnoliopsida', class),
order = ifelse(grepl('cinnamon', ignore.case=T, group), 'Canellales', order)) %>%
mutate(phylum = ifelse(grepl('tree|shrub|vascular|angio|spermato|flower', ignore.case=T, group),
'Tracheophyta', phylum)) %>%
mutate(phylum = ifelse(grepl('ferns', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('ferns', ignore.case=T, group), 'Polypodiopsida', class)) %>%
mutate(phylum = ifelse(grepl('conif', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('conif', ignore.case=T, group), 'Pinopsida', class)) %>%
mutate(phylum = ifelse(grepl('palm', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('palm', ignore.case=T, group), 'Liliopsida', class),
order = ifelse(grepl('palm', ignore.case=T, group), 'Arecales', order)) %>%
mutate(class = ifelse(grepl('monocot', ignore.case=T, group), 'Tracheophyta', class)) Check Event fields
The fields is: year
- Check it has numeric values.
raw_metadata %>%
janitor::clean_names() %>%
janitor::remove_empty(c('rows', 'cols')) %>%
mutate(year = ifelse(year == 'NA', NA, year)) %>%
mutate(year = ifelse(year == '2024?', NA, year)) %>%
mutate(year = ifelse(name_orig == 'The Red List of Mammals of South Africa, Swaziland and Lesotho 2024',
2024, year)) %>%
mutate(year = as.numeric(year, na.rm=T)) %>%
filter(is.na(year)) %>%
select(year, name_orig) %>%
distinct(name_orig, .keep_all = T) DOUBTS
https://www.odonat-grandest.fr/listes-rouges-grand-est-etat-avancement/
A Red List of Benin’s sharks
The Red List of Mammals of South Africa, Swaziland and Lesotho 2024
1 Crveni popis hrvatskih koralja
2 Crveni popis lišajeva Hrvatske
3 Červené seznamy
4 Coleoptera (Beetle) – Invertebrate Ireland Online
5 Tricoptera (Caddisfly) – InvertebrateIreland Online
6 Les mammifères de la Côte d’Ivoire
7 Rongeurs et insectivores de Côte d’Ivoire, leur habitat et leur statut de conservation
8 Красная книга Азербайджанской Республики
9 Красная книга Узбекистана
Check if URLs are working
# URL incorrect
raw_metadata %>%
filter(!grepl('http', url_clean)) %>%
distinct(url_clean)# A tibble: 3 × 1
url_clean
<chr>
1 NA
2 ima.sc.gov.br/index.php/biodiversidade/biodiversidade/fauna
3 <NA>
# URL error
# raw_metadata %>% filter(grepl('http', url_clean)) %>%
# distinct(url_clean) %>%
# mutate(check_URL = ifelse(map(URLencode(url_clean), http_error), 'not found', 'OK')) %>%
# filter(check_URL == 'not found')
raw_metadata %>%
filter(!grepl('http', url_clean)) %>%
distinct(url_clean)# A tibble: 3 × 1
url_clean
<chr>
1 NA
2 ima.sc.gov.br/index.php/biodiversidade/biodiversidade/fauna
3 <NA>
raw_metadata %>%
mutate(url_clean = ifelse(grepl('Nicolau', url_clean), NA, url_clean)) %>%
filter(!grepl('http', url_clean)) %>%
distinct(url_clean)# A tibble: 3 × 1
url_clean
<chr>
1 NA
2 ima.sc.gov.br/index.php/biodiversidade/biodiversidade/fauna
3 <NA>
DOUBTS
ima.sc.gov.br/index.php/biodiversidade/biodiversidade/fauna
Nicolau, J. i Dalmau, J., 2008. Llista Vermella\r\ndels Vertebrats d’Andorra. BIOCOM (Biologia i\r\nComunicació) SL i Departament de Patrimoni\r\nNatural del Govern d’Andorra. Informe inèdit
Run code and keep relevant fields
metadata <-
# check taxon
left_join(raw_metadata %>% mutate(group = str_trim(group)) %>%
select(-c(kingdom,phylum,subphylum,class,order)),
bind_rows(merged_list %>% filter(!is.na(scientificName)),
merged_list %>% filter(is.na(scientificName)) %>%
select(group) %>%
left_join(. , raw_metadata_taxon_list))) %>%
mutate(group = str_trim(group)) %>%
mutate(group = str_to_title(group)) %>%
mutate(group = str_replace_all(group, 'And ', 'and ')) %>%
mutate(group = str_replace_all(group, 'Of', 'of')) %>%
mutate(group = str_replace_all(group, 'The', 'the')) %>%
# more taxonomic corrections
mutate(group = str_squish(group)) %>%
mutate(kingdom = case_when(grepl('flora', group, ignore.case=T) ~ 'Plantae',
grepl('fauna', group, ignore.case=T) ~ 'Animalia',
.default = kingdom)) %>%
mutate(phylum = ifelse(phylum == 'chordata', 'Chordata', phylum)) %>%
mutate(kingdom = ifelse(group == 'Flora', 'Plantae', kingdom)) %>%
mutate(kingdom = ifelse(group == 'Fauna', 'Animalia', kingdom)) %>%
mutate(phylum = ifelse(group == 'Flora' | group == 'Fauna', NA, phylum)) %>%
mutate(phylum = ifelse(group =='Onychophora', 'Onychophora', phylum)) %>%
mutate(group = ifelse(group =='Opilioness', 'Opiliones', group)) %>%
mutate(group = ifelse(group =='False scorpions', 'Pseudoscorpiones', group)) %>%
mutate(order = ifelse(group =='False scorpions', 'Pseudoscorpiones', order)) %>%
mutate(class = ifelse(group =='Entomostraca', NA, class)) %>%
mutate(class = ifelse(group =='Horseshoe Crabs', 'Merostomata', class)) %>%
mutate(class = ifelse(group =='Freshwater Crabs', 'Malacostraca', class)) %>%
mutate(class = ifelse(group =='Sharks', 'Chondrichthyes', class)) %>%
mutate(order = ifelse(iso_2 == 'KE' & group == 'Carnivores', 'Carnivora', order),
order = ifelse(iso_2 == 'KE' & group == 'Perissodactyla', 'Perissodactyla', order),
order = ifelse(iso_2 == 'KE' & group == 'Marine Cetartiodactyla', 'Artiodactyla', order),
order = ifelse(iso_2 == 'KE' & group == 'Terrestrial Cetartiodactyla', 'Artiodactyla', order)) %>%
mutate(group = ifelse(group == 'Marine Cetartiodactyla', 'Cetaceans', group),
group = ifelse(group == 'Terrestrial Cetartiodactyla', 'Ungulates', group)) %>%
mutate(order = ifelse(group =='Endemic Lizards', 'Squamata', order)) %>%
mutate(class = ifelse(grepl('lamprey', ignore.case=T, group), 'Petromyzonti', class),
order = ifelse(grepl('lamprey', ignore.case=T, group), 'Petromyzontiformes', order)) %>%
mutate(group = ifelse(group == 'Musslels', 'Mussels', group)) %>%
mutate(phylum = ifelse(grepl('orchid', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('orchid', ignore.case=T, group), 'Liliopsida', class),
order = ifelse(grepl('orchid', ignore.case=T, group), 'Asparagales', order)) %>%
mutate(phylum = ifelse(grepl('bromeli', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('bromeli', ignore.case=T, group), 'Liliopsida', class)) %>%
mutate(phylum = ifelse(grepl('cinnamon', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('cinnamon', ignore.case=T, group), 'Magnoliopsida', class),
order = ifelse(grepl('cinnamon', ignore.case=T, group), 'Canellales', order)) %>%
mutate(phylum = ifelse(grepl('tree|shrub|vascular|angio|spermato|flower', ignore.case=T, group),
'Tracheophyta', phylum)) %>%
mutate(phylum = ifelse(grepl('ferns', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('ferns', ignore.case=T, group), 'Polypodiopsida', class)) %>%
mutate(phylum = ifelse(grepl('conif', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('conif', ignore.case=T, group), 'Pinopsida', class)) %>%
mutate(phylum = ifelse(grepl('palm', ignore.case=T, group), 'Tracheophyta', phylum),
class = ifelse(grepl('palm', ignore.case=T, group), 'Liliopsida', class),
order = ifelse(grepl('palm', ignore.case=T, group), 'Arecales', order)) %>%
mutate(class = ifelse(grepl('monocot', ignore.case=T, group), 'Tracheophyta', class)) %>%
# check columns
janitor::clean_names() %>%
janitor::remove_empty(c('rows', 'cols')) %>%
# check source
mutate(name_orig = str_squish(name_orig)) %>%
mutate(name_orig = str_remove_all(name_orig, "\\\\")) %>%
mutate(name_orig = str_remove_all(name_orig, "\"")) %>%
# missing name of source
mutate(name_orig = case_when(grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Birds' ~
'Liste rouge des Oiseaux du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Mammals' ~
'Liste rouge des Mammifères du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Orthoptera' ~
'Liste rouge des Orthoptères du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Fishes' ~
'Liste rouge des Papillons de jour (Rhopalocères et Zygènes) du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Butterflies' ~
'Liste rouge des Papillons de nuit du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Night butterflies' ~
'Liste rouge des Hétérocères du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Ladybugs' ~
'Liste rouge des Coccinelles du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Branchiopoda' ~
'Liste rouge des Branchiopodes du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Heteroptera' ~
'Liste rouge des Punaises du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Mayflies' ~
'Liste rouge des Ephémères – Trichoptères – Plécoptères du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Caddisflies' ~
'Liste rouge des Ephémères – Trichoptères – Plécoptères du Grand Est',
grepl('htt', name_orig) &
state_province == 'Grand Est' & group == 'Stoneflies' ~
'Liste rouge des Ephémères – Trichoptères – Plécoptères du Grand Est',
.default = name_orig)) %>%
# check format
mutate(format = ifelse(format == 'NA', NA, str_squish(format))) %>%
mutate(format = ifelse(format == '?', NA, format)) %>%
# check language
mutate(language = ifelse(language == 'NA', NA, str_squish(language))) %>%
mutate(language = str_replace(language, "/|\\|", ' | ')) %>%
# check location
mutate(continent = str_squish(str_replace_all(str_squish(continent), '\\|', ' | '))) %>%
mutate(continent = str_replace_all(continent, '_', ' ')) %>%
mutate(continent = str_to_title(continent)) %>%
mutate(country = ifelse(country == 'NA', NA, str_squish(country))) %>%
mutate(country = str_replace_all(country, '_', ' ')) %>%
mutate(country = ifelse(country == 'USSR', NA, str_to_title(country))) %>%
mutate(country = str_replace_all(country, 'And ', 'and ')) %>%
mutate(country = str_replace_all(country, 'Of', 'of')) %>%
mutate(country = str_replace_all(country, 'The', 'the')) %>%
mutate(state_province = ifelse(state_province == 'NA', NA, str_squish(state_province))) %>%
mutate(state_province = str_to_title(state_province)) %>%
mutate(iso_2 = ifelse(iso_2 == 'NA' & country != 'Namibia', NA, str_squish(iso_2))) %>%
mutate(iso_3 = ifelse(iso_3 == 'NA', NA, str_squish(iso_3))) %>%
mutate(iso_2 = str_squish(str_replace_all(str_squish(iso_2), '\\|', ' | '))) %>%
mutate(iso_3 = str_squish(str_replace_all(str_squish(iso_3), '\\|', ' | '))) %>%
mutate(gadm_level_1 = ifelse(gadm_level_1 == 'NA', NA, str_squish(gadm_level_1))) %>%
mutate(gadm_level_1 = str_to_title(gadm_level_1)) %>%
mutate(gadm_level_1 = str_replace_all(gadm_level_1, 'And ', 'and ')) %>%
mutate(gadm_level_1 = str_replace_all(gadm_level_1, 'Of', 'of')) %>%
mutate(gadm_level_1 = str_replace_all(gadm_level_1, 'The', 'the')) %>%
mutate(gadm_level_2 = ifelse(gadm_level_2 == 'NA', NA, str_squish(gadm_level_2))) %>%
mutate(gadm_level_2 = str_to_title(gadm_level_2)) %>%
mutate(region_custom = ifelse(region_custom == 'NA', NA, str_squish(region_custom))) %>%
mutate(region_detail = ifelse(region_detail == 'NA', NA, str_squish(region_detail))) %>%
mutate(region_detail = str_squish(str_replace_all(str_squish(region_detail), '\\|', ' | '))) %>%
# check event
mutate(year = ifelse(year == 'NA', NA, year)) %>%
mutate(year = ifelse(year == '2024?', NA, year)) %>%
mutate(year = ifelse(name_orig == 'The Red List of Mammals of South Africa, Swaziland and Lesotho 2024',
2024, year)) %>%
mutate(year = as.numeric(year, na.rm=T)) %>%
# check urls
mutate(url_clean = ifelse(url_clean == 'NA', NA, url_clean)) %>%
mutate(url_clean = ifelse(grepl('Nicolau', url_clean), NA, url_clean)) %>%
# select columns
select(id, continent,
gadm_level_0 = country, gadm_level_1, gadm_level_2,
region_custom, region_detail, iso_2, iso_3,
taxa=group, kingdom, phylum, class, order, family,
source_name= name_orig, source_link = url_clean,
language, year)
metadata %>% slice_sample(n=50) %>% arrange(id) %>%
kableExtra::kbl(booktabs = T) %>%
kableExtra::kable_styling(latex_options = c('striped', 'hold_position'))| id | continent | gadm_level_0 | gadm_level_1 | gadm_level_2 | region_custom | region_detail | iso_2 | iso_3 | taxa | kingdom | phylum | class | order | family | source_name | source_link | language | year |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 13 | Europe | Spain | ES | ESP | Bryophytes | Plantae | The 2006 Red List and an Updated Checklist of Bryophytes of the Iberian Peninsula (Portugal, Spain and Andorra) | https://www.researchgate.net/profile/Cecilia-Sergio-2/publication/259799050_The_2006_Red_List_and_an_Updated_Checklist_of_Bryophytes_of_the_Iberian_Peninsula_Portugal_Spain_and_Andorra/links/53f27b040cf2bc0c40ead6bc/The-2006-Red-List-and-an-Updated-Checklist-of-Bryophytes-of-the-Iberian-Peninsula-Portugal-Spain-and-Andorra.pdf | English | 2006 | ||||||||
| 373 | North America | Guadeloupe | GP | GLP | Terrestrial Reptiles | Animalia | Chordata | Reptilia | Liste rouge des reptiles terrestres de la Guadeloupe (France) | https://inpn.mnhn.fr/espece/listerouge/FR/Reptiles_terrestres_Guadeloupe_2021 | French | 2021 | ||||||
| 383 | North America | Martinique | MQ | MTQ | Odonata | Animalia | Arthropoda | Insecta | Odonata | Liste rouge des libellules de la Martinique (France) | https://inpn.mnhn.fr/espece/listerouge/FR/Odonates_Martinique_2020 | French | 2020 | |||||
| 438 | Europe | France | Corse | FR | FRA | Breeding Birds | Animalia | Chordata | Aves | Liste rouge des Oiseaux nicheurs de Corse | https://inpn.mnhn.fr/docs/LR_FCE/LR_regionale/Corse/LRR_oiseaux_nicheurs_amphibiens_reptiles_Corse_2018.pdf | French | 2017 | |||||
| 474 | Europe | France | Île-De-France | FR | FRA | Odonata | Animalia | Arthropoda | Insecta | Odonata | Liste rouge des Libellules d'Ile-de-France | https://www.arb-idf.fr/nos-travaux/publications/liste-rouge-regionale-des-libellules-dile-de-france/ | French | 2014 | ||||
| 627 | Europe | Czechia | CZ | CZE | Mammals | Animalia | Chordata | Mammalia | Červený seznam savců České republiky | https://www.researchgate.net/publication/331552011_Cerveny_seznam_savcu_Ceske_republiky_The_Red_List_of_mammals_of_the_Czech_Republic_Priroda_Praha_34_155-176 | Czech | 2019 | ||||||
| 681 | Europe | United Kingdom | GB | GBR | Orthoptera | Animalia | Arthropoda | Insecta | Orthoptera | A review of the Orthoptera (Grasshoppers and crickets) and allied species of Great Britain (NECR187) | https://publications.naturalengland.org.uk/publication/5368778738106368?category=4707656804597760 | English | 2015 | |||||
| 790 | Europe | Sweden | Västerbotten | SE | SWE | Flora | Plantae | SLU Artdatabanken (2020). Rödlista 2020 | https://artfakta.se/sok | Swedish | 2020 | |||||||
| 793 | Europe | Sweden | Pite lappmark | SE | SWE | Fauna | Animalia | SLU Artdatabanken (2020). Rödlista 2020 | https://artfakta.se/sok | Swedish | 2020 | |||||||
| 827 | Europe | Portugal | PT | PRT | Amphibians | Animalia | Chordata | Amphibia | Livro Vermelho dos Vertebrados de Portugal | https://www.icnf.pt/api/file/doc/17e63e4ea59d25ef | Portuguese | 2005 | ||||||
| 849 | Europe | Border zone with Moldova & Romania | Moldova | Romania | MD | RO | MDA | ROU | Fauna | Animalia | Lista rosie a speciilor de fl ora si fauna salbatica din zona de grania România – Republica Moldova | https://www.yumpu.com/it/document/view/14047287/lista-rosie-management-comun-romania# | Romanian | 2008 | |||||||
| 997 | Europe | Germany | Baden-Württemberg | DE | DEU | Mantodea | Animalia | Arthropoda | Insecta | Mantodea | Rote Liste und kommentiertes Verzeichnis der Heuschrecken und Fangschrecken Baden-Württembergs | https://www.lubw.baden-wuerttemberg.de/natur-und-landschaft/rote-listen | German | 2019 | ||||
| 1015 | Europe | Germany | Baden-Württemberg | DE | DEU | Red Algae | Plantae | Erlauterungen zur Roten Liste der limnischen Rot- und Braunalgen Baden-Württembergs | https://www.lubw.baden-wuerttemberg.de/natur-und-landschaft/rote-listen | German | 2019 | |||||||
| 1037 | Europe | Germany | Bayern | DE | DEU | Cucujoidea | Animalia | Arthropoda | Insecta | Coleoptera | Rote Liste gefährdeter Cucujoidea (Coleoptera: „Clavicornia“) Bayerns | https://www.lfu.bayern.de/natur/rote_liste_tiere/2003/index.htm | German | 2003 | ||||
| 1043 | Europe | Germany | Bayern | DE | DEU | Leaf Beetles | Animalia | Arthropoda | Insecta | Coleoptera | Rote Liste gefährdeter Blatt- und Samenkäfer (Coleoptera: Chrysomelidae et Bruchidae) Bayerns | https://www.lfu.bayern.de/natur/rote_liste_tiere/2003/index.htm | German | 2003 | ||||
| 1178 | Europe | Germany | Brandenburg | DE | DEU | Water Beetles | Animalia | Arthropoda | Insecta | Coleoptera | Rote Liste und Artenliste der Wasserkäfer des Landes Brandenburg (Coleoptera: Hydradephaga, Hydrophiloidea part., Dryoopoidea part. und Hydraenidae) | https://lfu.brandenburg.de/lfu/de/ueber-uns/veroeffentlichungen/detail/~01-01-2000-zeitschrift-naturschutz-und-landschaftspflege-in-brandenburg-beilage-zu-heft-3-2000 | German | 2000 | ||||
| 1217 | Europe | Germany | Niedersachsen | DE | DEU | Vascular Plants | Plantae | Tracheophyta | Referenzliste Gefäßpflanzen | https://www.nlwkn.niedersachsen.de/artenreferenzlisten/arten-referenzlisten-198326.html | German | 2021 | ||||||
| 1218 | Europe | Germany | Bremen | DE | DEU | Bryophytes | Plantae | Referenzliste Moose | https://www.nlwkn.niedersachsen.de/artenreferenzlisten/arten-referenzlisten-198326.html | German | 2022 | |||||||
| 1324 | Europe | Germany | Hessen | DE | DEU | Amphibians | Animalia | Chordata | Amphibia | Rote Liste der Säugetiere, Reptilien und Amphibien | https://www.hlnug.de/themen/naturschutz/rote-listen | German | 1996 | |||||
| 1326 | Europe | Germany | Hessen | DE | DEU | Mammals | Animalia | Chordata | Mammalia | Rote Liste der Säugetiere, Reptilien und Amphibien | https://www.hlnug.de/themen/naturschutz/rote-listen | German | 1996 | |||||
| 1428 | Europe | Germany | Nordrhein-Westfalen | DE | DEU | Wasps | Animalia | Arthropoda | Insecta | Hymenoptera | Rote Liste und Gesamtartenliste der Wildbienen und Wespen - Hymenoptera - Aculeata - in Nordrhein-Westfalen | https://www.lanuk.nrw.de/themen/natur/artenschutz/rote-liste | German | 2009 | ||||
| 1431 | Europe | Germany | Nordrhein-Westfalen | DE | DEU | Heteroptera | Animalia | Arthropoda | Insecta | Diptera | Sphaeroceridae | Kommentiertes Artenverzeichnis der Wanzen - Heteroptera - in Nordrhein-Westfalen | https://www.lanuk.nrw.de/themen/natur/artenschutz/rote-liste | German | 2011 | |||
| 1454 | Europe | Germany | Saarland | DE | DEU | Characeae | Plantae | Charophyta | Charophyceae | Charales | Characeae | Rote Liste und Gesamtartenliste der Armleuchteralgen (Charophyceae) des Saarlandes - 3. Fassung | https://rote-liste-saarland.de/ | German | 2020 | |||
| 1459 | Europe | Germany | Saarland | DE | DEU | Reptiles | Animalia | Chordata | Reptilia | Rote Liste und Gesamtartenliste der Reptilien (Reptilia) des Saarlandes – 3. Fassung | https://rote-liste-saarland.de/ | German | 2020 | |||||
| 1500 | Europe | Germany | Sachsen | DE | DEU | Lichens | Plantae | Rote Liste Flechten | https://publikationen.sachsen.de/bdb/artikel/41195 | German | 1996 | |||||||
| 1533 | Europe | Germany | Sachsen | DE | DEU | Hoverflies | Animalia | Arthropoda | Insecta | Diptera | Rote Liste Schwebfliegen | https://publikationen.sachsen.de/bdb/artikel/39280 | German | 1996 | ||||
| 1626 | Europe | Germany | Sachsen-Anhalt | DE | DEU | Chrysomelidae | Animalia | Arthropoda | Insecta | Coleoptera | Chrysomelidae | Rote Listen Sachsen-Anhalt 2020 | https://lau.sachsen-anhalt.de/alt-vor-neuer-navigation/wir-ueber-uns-publikationen/fachpublikationen/berichte-des-lau/rote-listen-sachsen-anhalt-2048 | German | 2020 | |||
| 1631 | Europe | Germany | Sachsen-Anhalt | DE | DEU | Ants | Animalia | Arthropoda | Insecta | Hymenoptera | Rote Listen Sachsen-Anhalt 2020 | https://lau.sachsen-anhalt.de/alt-vor-neuer-navigation/wir-ueber-uns-publikationen/fachpublikationen/berichte-des-lau/rote-listen-sachsen-anhalt-2053 | German | 2020 | ||||
| 1802 | Europe | Germany | Thüringen | DE | DEU | Ptinidae | Animalia | Arthropoda | Insecta | Coleoptera | Ptinidae | Rote Liste der Aaskäfer, Nestkäfer, Poch- und Diebskäfer, Scheinbockkäfer, Düsterkäfer, Schwarzkäfer (Insecta: Coleoptera: Silphidae, Leiodidae pt., Ptinidae, Oedemeridae, Melandryidae, Tenebrionidae) und weiterer Käferfamilien Thüringens 2011 | https://tlubn.thueringen.de/naturschutz/rote-listen/kaefer | German | 2011 | |||
| 1879 | Europe | Germany | Thüringen | DE | DEU | Myxomycetes | Protozoa | Mycetozoa | Myxomycetes | Rote Liste der Schleimpilze (Myxomycetes) Thüringens 2010 | https://tlubn.thueringen.de/naturschutz/rote-listen/pilze | German | 2010 | |||||
| 1889 | Europe | Liechtenstein | LI | LIE | Orchids | Plantae | Tracheophyta | Liliopsida | Asparagales | Orchideen des Fürstentums Liechtenstein | https://www.llv.li/serviceportal2/amtsstellen/amt-fuer-umwelt/publikationen/naturkindliche-forschung/b13-orchideen.pdf | German | 2000 | |||||
| 1942 | South America | Brazil | Paraná | BR | BRA | Flora | Plantae | Lista de Ameaça de Flora e Fauna do Estado do Paraná. Última avaliação da Flora (2008) e da Fauna (2010). | https://specieslist.sibbr.gov.br/speciesListItem/list/drt1572895366472 | Portuguese | 2008 | |||||||
| 2078 | Africa | Tanzania | TZ | TZA | Endemic Reptiles | Animalia | Chordata | Reptilia | Tanzania's reptile biodiversity: Distribution, threats and climate change vulnerability | https://www.researchgate.net/publication/303288672_Tanzania%27s_reptile_biodiversity_Distribution_threats_and_climate_change_vulnerability | English | 2016 | ||||||
| 2154 | Asia | Iraq | IQ | IRQ | Selected Species In Marshlands | Plantae | Regional red list assessment of selected species in the Iraqi marshlands | https://www.academia.edu/42250427/Regional_red_list_assessment_of_selected_species_in_the_Iraqi_marshlands | English | 2013 | ||||||||
| 2155 | Asia | Viet Nam | VN | VNM | Flora | Plantae | Vietnam Red Data Book. Part II. Plants | http://vuonquocgiachumomray.vn/upload/104881/20221227/SACHDOVN-PHANII_9924e.pdf | Vietnamese | 2007 | ||||||||
| 2158 | Asia | Viet Nam | VN | VNM | Flora | Plantae | Red Data Book 2004 of Vietnam | https://www.researchgate.net/publication/285304215_Red_Data_Book_2004_of_Vietnam | Vietnamese | 2004 | ||||||||
| 2255 | Oceania | Australia | Northern Territory | AU | AUS | Flora | Plantae | Commonwealth, State and Territory listed threatened species report | https://www.environment.gov.au/sprat-public/action/report | English | 2014 | |||||||
| 2297 | Europe | Carpathians | Austria | Czechia | Poland | Slovakia | Ukraine | Romania | AT | CZ | PL | SK | UA | RO | AUT | CZE | POL | SVK | UKR | ROU | Vascular Plants | Plantae | Tracheophyta | Carpathian List of Endangered Species | https://archive.nationalredlist.org/files/2012/08/Carpathian-List-of-Endangered-Species-2003.pdf | English | 2003 | ||||||
| 2519 | Europe | Poland | Silesian | PL | POL | Odonata | Animalia | Arthropoda | Insecta | Odonata | Czerwone listy wybranych grup zwierząt bezkręgowych | https://www.sbc.org.pl/dlibra/publication/180509 | Polish | 2012 | ||||
| 2689 | South America | Argentina | Tandilia Mountains | AR | ARG | Reptiles | Animalia | Chordata | Reptilia | An annotated list of the reptiles of the highland grassland of Tandilia Mountains, Argentina | https://ri.conicet.gov.ar/handle/11336/139060 | English | 2021 | |||||
| 2851 | Asia | Bangladesh | BD | BGD | Mammals | Animalia | Chordata | Mammalia | Red List of Threatened Animals of Bangladesh | https://portals.iucn.org/library/node/7786 | English | 2000 | ||||||
| 2912 | Asia | Japan | JP | JPN | Reptiles | Animalia | Chordata | Reptilia | レッドリスト2018 | https://ikilog.biodic.go.jp/Rdb/booklist | Japanese | 2018 | ||||||
| 2925 | Asia | Japan | JP | JPN | Crustaceans | Animalia | Arthropoda | 海洋生物レッドリスト(2017) | https://ikilog.biodic.go.jp/Rdb/booklist | Japanese | 2017 | |||||||
| 2954 | Asia | Japan | JP | JPN | Mammals | Animalia | Chordata | Mammalia | レッドリスト2012 | https://ikilog.biodic.go.jp/Rdb/booklist | Japanese | 2012 | ||||||
| 3086 | Asia | Russia | Dagestan | RU | RUS | Flora | Plantae | Красная книга Республики Дагестан. Редкие, находящиеся под угрозой исчезновения виды животных и растений. Махачкала, 1998. | https://www.plantarium.ru/lang/en/page/redbook/id/233.html | Russian | 1998 | |||||||
| 3102 | Asia | Russia | Zabaykal'ye | RU | RUS | Flora | Plantae | Перечень объектов растительного мира, занесенных в Красную книгу Забайкальского края (в редакции постановления Правительства Забайкальского края от 04 февраля 2014 года № 20). | https://www.plantarium.ru/lang/en/page/redbook/id/231.html | Russian | 2014 | |||||||
| 3148 | Europe | Russia | Krasnodar | RU | RUS | Fauna | Animalia | Красная книга Краснодарского края | https://www.cerambyx.uochb.cz/assets/pdf/collective_2017_krasnaya_kniga_zhivotnie.pdf | Russian | 2017 | |||||||
| 3174 | Europe | Russia | Moscow City | RU | RUS | Flora | Plantae | Список редких, находящихся под угрозой исчезновения и уязвимых в условиях города Москвы видов животных и растений, занесенных в Красную книгу города Москвы. Приложение 2 к постановлению Правительства Москвы от 2 июля 2019 г. № 745-ПП | https://www.plantarium.ru/page/redbook/id/289.html | Russian | 2019 | |||||||
| 3241 | Europe | Russia | Tambov | RU | RUS | Flora | Plantae | Красная книга Тамбовской области: Растения, лишайники, грибы. Тамбов, 2002. | https://www.plantarium.ru/lang/en/page/redbook/id/236.html | Russian | 2002 | |||||||
| 3268 | Europe | Russia | Ul'yanovsk | RU | RUS | Flora | Plantae | Красная книга Ульяновской области. Москва, 2015. | https://www.plantarium.ru/lang/en/page/redbook/id/240.html | Russian | 2015 |
Data audit
Summary
Code
metadata %>%
summarise(`Number of records` = n(),
`Number of sources` = n_distinct(source_name),
`Number of taxa` = n_distinct(taxa),
`Animalia records` = sum(kingdom == 'Animalia'),
`Plantae records` = sum(kingdom == 'Plantae'),
`Fungi records` = sum(kingdom == 'Fungi'),
Countries = n_distinct(gadm_level_0),
`Sub-national territories` = n_distinct(gadm_level_1)) %>%
t() %>% `colnames<-`(c("N")) %>%
kableExtra::kbl(booktabs = T) %>%
kableExtra::kable_styling(latex_options = c('striped', 'hold_position'))| N | |
|---|---|
| Number of records | 3200 |
| Number of sources | 2091 |
| Number of taxa | 483 |
| Animalia records | 2189 |
| Plantae records | 899 |
| Fungi records | 105 |
| Countries | 170 |
| Sub-national territories | 223 |
Geographic coverage
Code
metadata %>%
separate_rows(continent, sep = '\\|') %>%
mutate(continent = str_squish(continent)) %>%
group_by(continent) %>%
summarise(n_sources = ifelse(n_distinct(source_name, na.rm = TRUE)==0,
0, n_distinct(source_name, na.rm = TRUE))) %>%
arrange(desc(n_sources)) %>%
rename(`Number of sources`=n_sources) %>%
adorn_totals('row') %>%
kableExtra::kbl(booktabs = T) %>%
kableExtra::kable_styling(latex_options = c('striped', 'hold_position')) | continent | Number of sources |
|---|---|
| Europe | 1439 |
| Asia | 272 |
| Africa | 143 |
| South America | 116 |
| North America | 112 |
| Oceania | 31 |
| Antarctica | 7 |
| Total | 2120 |
Code
metadata %>%
separate_rows(continent, sep = '\\|') %>%
mutate(continent = str_squish(continent)) %>%
group_by(continent) %>%
summarise(n_records = n()) %>%
arrange(desc(n_records)) %>%
rename(`Number of records`=n_records) %>%
adorn_totals('row') %>%
kableExtra::kbl(booktabs = T) %>%
kableExtra::kable_styling(latex_options = c('striped', 'hold_position')) | continent | Number of records |
|---|---|
| Europe | 2182 |
| Asia | 470 |
| Africa | 205 |
| North America | 156 |
| South America | 150 |
| Oceania | 62 |
| Antarctica | 7 |
| Total | 3232 |
Code
# Europe
metadata %>%
separate_rows(continent, sep = '\\|') %>%
mutate(continent = str_squish(continent)) %>%
filter(continent == 'Europe') %>%
group_by(kingdom) %>%
summarise(n_records = n()) %>%
arrange(desc(n_records)) %>%
rename(`Number of records`=n_records) %>%
adorn_totals('row') %>%
kableExtra::kbl(booktabs = T) %>%
kableExtra::kable_styling(latex_options = c('striped', 'hold_position')) | kingdom | Number of records |
|---|---|
| Animalia | 1551 |
| Plantae | 549 |
| Fungi | 75 |
| Protozoa | 6 |
| Chromista | 1 |
| Total | 2182 |
Code
metadata %>%
separate_rows(continent, sep = '\\|') %>%
mutate(continent = str_squish(continent)) %>%
filter(continent == 'Asia') %>%
group_by(kingdom) %>%
summarise(n_records = n()) %>%
arrange(desc(n_records)) %>%
rename(`Number of records`=n_records) %>%
adorn_totals('row') %>%
kableExtra::kbl(booktabs = T) %>%
kableExtra::kable_styling(latex_options = c('striped', 'hold_position'))| kingdom | Number of records |
|---|---|
| Animalia | 277 |
| Plantae | 175 |
| Fungi | 18 |
| Total | 470 |
Code
world <- geodata::world(resolution = 3, level = 0, path = 'data/')
world_records <- left_join(st_as_sf(world), metadata %>%
separate_rows(iso_3, sep = '\\|') %>%
select(iso_2, GID_0=iso_3, source_name)) %>%
group_by(GID_0, NAME_0) %>%
summarise(n_sources = ifelse(n_distinct(source_name, na.rm = TRUE)==0,
0, n_distinct(source_name, na.rm = TRUE)),
iso_2_string = ifelse(n_sources>0,
paste(iso_2, collapse = ';'), NA)) %>%
ungroup() %>% st_cast() %>% st_set_crs(4326)
plot_figure_1 <- tm_shape(world_records %>%
select(-iso_2_string) %>%
mutate(n_sources=ifelse(n_sources==0,
NA, n_sources))) +
tm_polygons(fill = 'n_sources',fill_alpha = 0.9,
col='grey40', col_alpha = 0.2,
fill.scale = tm_scale_intervals(n = 6,
#style = 'jenks',
breaks = c(1,5,10,20,100,979),
values = 'brewer.reds',
value.na = 'grey80',
label.na = '0'),
fill.legend = tm_legend(item.space = 0, item.na.space = 0,
title = 'Number of sources',
reverse=T,
# frame=F,
frame.lwd = 0.1,
bg.color = 'white')) +
tm_layout(legend.outside = T,
legend.position = c('left','bottom'), frame=F) +
tm_crs(property='global')
tmap_mode('plot')
plot_figure_1Code
tmap_mode('view')
plot_figure_1